A distributed dynamic brain network mediates linguistic tone representation and categorization

Gangyi Feng*, Zhenzhong Gan, Fernando Llanos, Danting Meng, Suiping Wang, Patrick C.M. Wong, Bharath Chandrasekaran

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Successful categorization requires listeners to represent the incoming sensory information, resolve the “blooming, buzzing confusion” inherent to noisy sensory signals, and leverage the accumulated evidence towards making a decision. Despite decades of intense debate, the neural systems underlying speech categorization remain unresolved. Here we assessed the neural representation and categorization of lexical tones by native Mandarin speakers (N = 31) across a range of acoustic and contextual variabilities (talkers, perceptual saliences, and stimulus-contexts) using functional magnetic imaging (fMRI) and an evidence accumulation model of decision-making. Univariate activation and multivariate pattern analyses reveal that the acoustic-variability-tolerant representations of tone category are observed within the middle portion of the left superior temporal gyrus (STG). Activation patterns in the frontal and parietal regions also contained category-relevant information that was differentially sensitive to various forms of variability. The robustness of neural representations of tone category in a distributed fronto-temporoparietal network is associated with trial-by-trial decision-making parameters. These findings support a hybrid model involving a representational core within the STG that operates dynamically within an extensive frontoparietal network to support the representation and categorization of linguistic pitch patterns.

Original languageEnglish (US)
Article number117410
StatePublished - Jan 1 2021


  • Categorization decision
  • Lexical tones
  • Neural decoding
  • Neural representation
  • Perceptual constancy
  • Speech categorization

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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